
nickduran (Nicholas Duran) - GitHub
Python library for extracting quantitative, reproducible metrics of multi-level alignment between speakers in naturalistic language corpora. R source code for replicating results reported in manuscript. Code written in R. Data accessible by permission.
GitHub - fxsjy/gonn: GoNN is an implementation of Neural …
GoNN is an implementation of Neural Network in Go Language, which includes BPNN, RBF, PCN
lightvector/GoNN: Sandbox for playing with neural nets for Go - GitHub
See here for a fully-working Alpha-Zero-like self-training loop that is a major continuation of the research and experimentation in this repo: https://github.com/lightvector/KataGo. This repo …
Breast cancer diagnosis using Genetically Optimized Neural Network ...
Jun 15, 2015 · In this paper, we propose a new, Genetically Optimized Neural Network (GONN) algorithm, for solving classification problems. We evolve a neural network genetically to optimize its architecture (structure and weight) for classification.
推荐文章:GoNN - 简单高效的Go语言神经网络库 - CSDN博客
May 24, 2024 · GoNN 是一个用Go语言实现的神经网络库,旨在提供高效且易于使用的神经网络模型,包括反向传播网络(BackPropagation Network)、径向基函数网络(RBF Network)以及感知机网络(Perceptron Network)。
GoNN:一个用Go语言实现的神经网络库 - Baidu
gonn是一个用go语言编写的神经网络库,它实现了bp网络、rbf网络和感知机等多种神经网络模型。 在MNIST手写体字符识别数据库上,GoNN达到了98.2%的正确率。
fxsjy-gonn: GoNN是一个用GO语言写的神经网络库 GoNN目前实 …
gonn是一个用go语言写的神经网络库 gonn目前实现了bp网络,rbf网络和感知机 在著名的手写体字符识别数据库mnist上,gonn达到了98.2%的正确率 展开 收起 暂无标签
GoNN | gonn
Neural network library for go. Neural network architecture name (required field for a config). The neuron bias, false or true (required field for a config). Array of the number of neurons in each hidden layer. ActivationMode function mode (required field for a config). The mode of calculation of the total error.
GoNN:用Go语言实现的神经网络库 - 百度智能云
Jan 7, 2024 · GoNN(Go Neural Network)是一个用Go语言实现的神经网络库。 它是一个相对较新的库,但已经在Go社区中引起了广泛的关注。 GoNN的目标是提供一个易于使用、高效且可扩展的神经网络库,用于解决各种机器学习问题。
GoNN:用Go语言实现的神经网络库-百度开发者中心 - Baidu
Jan 7, 2024 · gonn是一个用go语言编写的神经网络库,它实现了bp网络、rbf网络和感知机。 在MNIST手写体字符识别数据库上,GoNN达到了98.2%的正确率。 本文将介绍GoNN的基本概念、功能特点、使用方法和应用场景,以及与其他神经网络库的比较。